{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mlfinlab\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on package mlfinlab:\n",
      "\n",
      "NAME\n",
      "    mlfinlab - Package based on the text book: Advances in Financial Machine Learning, by Marcos Lopez de Prado\n",
      "\n",
      "PACKAGE CONTENTS\n",
      "    data_structures (package)\n",
      "    features (package)\n",
      "    filters (package)\n",
      "    labeling (package)\n",
      "    multi_product (package)\n",
      "    sample_weights (package)\n",
      "    sampling (package)\n",
      "    tests (package)\n",
      "    util (package)\n",
      "\n",
      "SUBMODULES\n",
      "    fracdiff\n",
      "    microstructural\n",
      "\n",
      "FILE\n",
      "    /Users/maksimivanov/research/Chapter19/mlfinlab/__init__.py\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date and Time</th>\n",
       "      <th>Price</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Market Flag</th>\n",
       "      <th>Sales Condition</th>\n",
       "      <th>Exclude Record Flag</th>\n",
       "      <th>Unfiltered Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ESH17</td>\n",
       "      <td>2017/01/02 17:00:00.077</td>\n",
       "      <td>2240.75</td>\n",
       "      <td>1360</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2240.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ESH17</td>\n",
       "      <td>2017/01/02 17:00:00.140</td>\n",
       "      <td>2241.00</td>\n",
       "      <td>1</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2241.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ESH17</td>\n",
       "      <td>2017/01/02 17:00:00.140</td>\n",
       "      <td>2241.00</td>\n",
       "      <td>5</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2241.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ESH17</td>\n",
       "      <td>2017/01/02 17:00:00.140</td>\n",
       "      <td>2241.00</td>\n",
       "      <td>1</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2241.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ESH17</td>\n",
       "      <td>2017/01/02 17:00:00.140</td>\n",
       "      <td>2240.75</td>\n",
       "      <td>15</td>\n",
       "      <td>E</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2240.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Symbol            Date and Time    Price  Volume Market Flag  \\\n",
       "0  ESH17  2017/01/02 17:00:00.077  2240.75    1360           E   \n",
       "1  ESH17  2017/01/02 17:00:00.140  2241.00       1           E   \n",
       "2  ESH17  2017/01/02 17:00:00.140  2241.00       5           E   \n",
       "3  ESH17  2017/01/02 17:00:00.140  2241.00       1           E   \n",
       "4  ESH17  2017/01/02 17:00:00.140  2240.75      15           E   \n",
       "\n",
       "   Sales Condition  Exclude Record Flag  Unfiltered Price  \n",
       "0                0                  NaN           2240.75  \n",
       "1                0                  NaN           2241.00  \n",
       "2                0                  NaN           2241.00  \n",
       "3                0                  NaN           2241.00  \n",
       "4                0                  NaN           2240.75  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "help(mlfinlab)\n",
    "# load data\n",
    "data = pd.read_csv('./ES.csv', nrows=100000)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Microstructure features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Market microstructure features aim to tease out useful information from the trading behavior of market participants on exchanges. These features have become more popular with the increased amount and granularity of data provided by exchanges. As a result, multiple models of liquidity, uncertainty, and price impact have emerged from this data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First generation: price sequences"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Tick Rule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# help(mlfinlab.features.microstructural)\n",
    "from mlfinlab.features.microstructural import tick_rule\n",
    "aggressor = tick_rule(data['Price'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Roll Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.6312040959303584, -0.7866401426532182)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mlfinlab.features.microstructural import roll_model\n",
    "spread, noise = roll_model(data['Price'])\n",
    "spread, noise\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### High-Low Volatility Estimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       date    price  volume\n",
      "0   2017/01/02 17:00:00.077  2240.75    1360\n",
      "1   2017/01/02 17:00:00.140  2241.00       1\n",
      "2   2017/01/02 17:00:00.140  2241.00       5\n",
      "3   2017/01/02 17:00:00.140  2241.00       1\n",
      "4   2017/01/02 17:00:00.140  2240.75      15\n",
      "5   2017/01/02 17:00:00.140  2240.75       2\n",
      "6   2017/01/02 17:00:00.140  2240.75       1\n",
      "7   2017/01/02 17:00:00.140  2240.75       3\n",
      "8   2017/01/02 17:00:00.140  2240.75       1\n",
      "9   2017/01/02 17:00:00.207  2241.00       8\n",
      "10  2017/01/02 17:00:00.207  2240.75       1\n",
      "11  2017/01/02 17:00:00.207  2241.00      30\n",
      "12  2017/01/02 17:00:00.207  2241.00       3\n",
      "13  2017/01/02 17:00:00.260  2241.25      19\n",
      "14  2017/01/02 17:00:00.260  2241.25       1\n",
      "15  2017/01/02 17:00:00.288  2241.00       1\n",
      "16  2017/01/02 17:00:00.288  2241.00       2\n",
      "17  2017/01/02 17:00:00.288  2241.25       1\n",
      "18  2017/01/02 17:00:00.288  2241.00       1\n",
      "19  2017/01/02 17:00:00.288  2241.00       2\n",
      "\n",
      "\n",
      "Rows: 100000\n",
      "Reading data in batches:\n",
      "Batch number: 0\n",
      "Returning bars \n",
      "\n",
      "Bars: 48818\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bbd9cf8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# first create some bars \n",
    "from mlfinlab.data_structures import get_dollar_bars\n",
    "from mlfinlab.features.microstructural import high_low_estimator\n",
    "\n",
    "date_time = data['Date and Time'] \n",
    "new_data = pd.concat([date_time, data['Price'], data['Volume']], axis=1)\n",
    "new_data.columns = ['date', 'price', 'volume']\n",
    "print(new_data.head(20))\n",
    "print('\\n')\n",
    "print('Rows:', new_data.shape[0])\n",
    "new_data.to_csv('./maks_tick_data.csv', index=False)\n",
    "\n",
    "th = 10000\n",
    "bars = get_dollar_bars('./maks_tick_data.csv', threshold=th, batch_size=1000000, verbose=True)\n",
    "print('Bars:', bars.shape[0])\n",
    "\n",
    "vol = high_low_estimator(bars.high, bars.low, window=50)\n",
    "plt.figure(figsize=(10, 5))\n",
    "vol.plot()\n",
    "plt.figure(figsize=(10, 5))\n",
    "bars.close.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Corwin-Shultz Algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bcda3c8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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khgHHCYPHVpT2zMaThulSKHdiYy3SJyJbOCatgMxahaJKIRpT+ItfjU7W2jEQQscA8Mgqe4XUn9lwAm/sPI1Lp1fhh5+dldX+pvrE3atd3R4AXPvbzWjoGETDPV80jNJSWxbz5We64vZOfzD5+0rZem17ZpNxiKi4sSWtgO5ZesRweSyW3OVpxG6aC9G6DHPRTZqLbSZSeiilcLw1ucqAUgp+n/FHtr0/fyk5rI5NqrHaCmJWMYPct66utdC7QEQFwCCtgPY0dRsujymV8QxFILmUVKk2OzQa837yV72uwTAeWFGXtKxnKGzakjbnztyNRUuVLjgNRqJo6UlOHTI2QzSgd4hBWj4opbDq8EiQ1swKFuQxA8EIS+DlCIO0HHl6wwlb64lBn97xtn7D8Vh2JaXwKIkf4ki0uEKFaExhb0oQG1OAz0b06nRc2tkeZz96kTQB7w//sBsfv3s1gpGRcWtjdXZndIy+Lq9JpHJJyEU5NKJs/OC1XfjCo+8hwM+m6xik5YHTn7Ifzd+T1fOFdUFEItmsvvWnqXPQsJi5l8SUGtViFY0pW2PSTllMLkjV3D06aW4695p0UwPA8oPxbuhfvD2SGLcng/QkxWCsduN6TWr3erFdcFHhbT3RMVxjORd2NsarxTBIcx+DtDw42+MsCMjWA8tHugkX7m0edf8n71uLv79/bT53yTGjcV9dgyFbxcrtzDzUt9I5belaa2O27lu7Rgq1/2a1vUkexYYNae6prlmMu5ccNrzvG7/fmvR3upZcolRKKVz39FZ8+4XanD1HIhdo5wDrFLuNQVqemKXMeHytcZmoT9yzJuPnWnHoHK6atwpbT3QML0sdJ+V1RkHa9U9vNVgzM/r0IasyrDVq1/G2/pxuv1DGajduofzOZIhEbyB57N/S/S2G69HY0RcI43MPrR8utZeNfDQSXDqtEsDIRDVyD4O0PPnioxsdrZ9NDrLGjkG09gVxnS6oWbzfPKGuF93y9v5RyzpydJWWq+0mhB10T/UFwliwoylp8oeX6Mfajbcxaa9tO2WrJTfXFtQ2FXoXKMfqW/tR39qPhywSfttR5ufPfDHj0SNP2ujCFaRdTlNq5NIv3jmAn721D7tNZv56iVcDyVzoHAjhF+/sx43Pj66/qxeLKTy38SSGHCQ8DluUR0vVPTQ2xzgCQNdACI+tPoZQxNtdugv3NqO6ZjFae3PTSpUYe6u/KBqLItGY48//eMMgjcalZt2MTi+V2mrri5/0i2EArofetpxLzKg80TaQdr3lB1twx6JDuHeZ+eSSVI85HLPo9QAmG0+tP44HVx7FmiPezgv3wz/sBgA8tsZ4uEq2EiXx3I5fqmsW471jzirg2JH4TM53mHT5r+9ajVm/XOr6/nT0B7H7VJfr2y0EBmk0Lt2vm1zhtBYnxXmpBTJfUgP6tXWtqK5ZjN9r48kSwVyPg9au012F70L1ioaOeBDc4jAtTqEMOi4RZ0+iJS0XrdX/71336+72aeMmzcZVmsnVUJMfv74HX31yc062nW8M0saRYCSaNNYtkxNAZIw0TffpBmOXmVQxoPQ4cQC48fkdAIB52szMRAvIO7vP2A5iOdh6RCKFzaM5aqFym90W72hMOZr52KWtm4sLoRPt6VuDM1Gah3FvrX0B9AXML37WH21Dg/ba3juWv+EyucZfp3Hklrf3DxcvB9J3Vy3dfxbVNYuTCpo/ua4eV/xyKZ4wmZFarFYfacWW4x3WK5qorlmM6prFLu5RcRgvMdpvVh3D39qcba2PtxI5Cq1kWo42GIni4ZVHi6Jr3KlcXgw+894JfO6h9a60UtlNLHzn4kP46K9X2n7OH86Pd6cWy+ScbEsqpwu+Eq6atxr/8MB60/tveG47vv3Cjux2xIMYpI0jb+86gymVpcN/J74Y4WgMvSlfkrd3nwEAHNSV+rhvWbyLUN9VOFa8sq0xb8/16fvX4n8+sy39Sh49N9fpst/nuruzZyg86nNZCA+vsj/DrkQXpdltacy0Ie0P207hN6uP4cl1xzPbgIflMja5c/Fh1Lf2uzIW1e6g9+c3NQCwP46zvT/ekjZeEkYHbY6ztKrRnItWwkJjkDbO+H0jvwinu4YQCEfxbwv24u/vS05umyi/ZPZDY+fKp5gs3pd9ihK7LYwNHYPYWN+OaEyhumYxfrd+5EfWqEyYlxw522e9kkv+9p41mPv4prw9n5EjLc7qETbofiTsBrElGUZpTdpYtp4xOKYyH6GJGxcZTrdhFbhvPNY+3NUJOG9JO9Ux6Gg8ZCHpW0ut3pfxNJM8lb/QO0CF86XHzHO3Jb40ZlebzCw92vObTjpaP3EV/uDKo/jep/48F7vkulJ//oLI/mAE/UF3irjHYgqBSBRVZc5OeasPO5tlOH/HSA4zN1rS0pUUe3Zj/PNW2zg2ZrHpuRFAfeQ/VuAT75+Bp775MRf2aMRgaOQz6WaQtubIuVFVAZwWl/j7+9fisulV2PCzf3D2wKw5Py/o3wmr1/mO1rMDxMsa9gyF8Z8unuL4OYsRW9LGGbsXJCu0LPyvbM1fN2Cxc5oaIfHjrL9KTFQn2HfGuELFeLH6sDtVIALhKALhKB5dcwyzb1vuuJXBaSOXfn27w6rSTRywE+iNlTxTD+sSt7pRRL5nKIxlB82rM+xo6DS9Lx19Djw7x0ef6+xoi3n1kXO9o7vyMpmc47R2caF06y5ArF6nvoX6k/etHdXA0FQkrzkTDNIore0nO8dEq1k+kkKmlu+xkuja1F+Mt2qzbxfuGV1z1Wty2QFhd9C9lStvXYYrb12GRVp3tt3ko0opKKUcd0Xq17c9u9PRM4xWLN1bVvQ1bo3edqXiwwMetcgrlzh2Vg41Z/YZ0x9jO+Pa9J+D5jSpRXwGLzrTFsUDZ3ryPKHE+X6GHHR3Bi0uRPQPH2sJgBmk0TCzL/VHf70yz3vivr/41TKc7iqeq61DLgUpueQ0caUTpS6nRalvjbdgnLQxsFgphctvWYI7Fx92NGttMBRJasWw2wriT3mSUx2DqK5ZjFdtTmYxaoEpduneunSlkhLHbt5i42L1epn2qCZNDnG4kXStnkaBaaZpbr702Eb8dMEeAHBU/aJQjLo7YzGFbVr96d+tT59/rbLMN3zbat1iwyBtnEnXMPDPaQqYj4Wrk8QPtdd4e6qAuZUuFabvC4TRkTJrK1f1Bu38pibWeW7TSUcTOTr6k1uc7baCpAakv3r3AADgl+8csP3cFJeIaZ7ZODI+1Ow4pAuAlFKmF60lusOVGNjfGwiPGj/Y2DEwqgZzJE0dX5/BFUFiCMXprkHsO+2sVNyOhvhYxe+9vNPR4xK2nejAqQ57F7bt/dn1thgdi99tOIF/fnorNhw1rpCgD5D1750+wXBqEP3esTZszmPJQTfYOhOKyDUiUici9SJSY3B/uYi8rt2/TUSqdffdoi2vE5GrrbYpIq9qyw+IyHMiUgpyTboLs71p6kXanSLtZelOkOTcQMidQf03vViLL6fM4nS7JS3BTstE4nSvlPFFzTPv2btStzszb1NKjr6jLe7MoL3mkQ2orlk8LipDzN9+CtU1iw1TtlxvcvGZrhXsla2NuPLWZWjuHt09qR9DmDinfPj2FfjIHSuS1vvioxtx4wvJtV670szENQzStJa3v7t37ajviJVEl2+mrfL//PRW/MsL6WvVZkPfJW30vTyhjc9t6Qng/Enlo+5/1aQlXz+x40Bz8tjebz67Hd+wSn/kMZZnQhHxAXgCwOcBzAZwvYjMTlntJgBdSqkrADwM4F7tsbMBXAfggwCuAfCkiPgstvkqgCsBfAhAJYDvZPUKKUmm41dUSozm9VQRRnJRo9Mqb89Yoz/ubr2d20924kzKj+GkitxMPHcasBj9cN5p0pWW+jvz8hZ73ZWp4+9aXCrafUQL9nrHyJi1dF7Y3ADAuMTWdpMJAuk+Cov3x8cwNhh0j+s/EWZBf2tvAP3BCA6cST62qV3bekaVTwJh84vjM91DOJBmglF7fyjrPINWtWrdYnQsEt/VmFL4zJXnj7r/VMcA/uX57WnPwWOhccHO5epVAOqVUieUUiEA8wHMTVlnLoAXtdtvAvisxC835gKYr5QKKqVOAqjXtme6TaXUEqUBsB3AJdm9RNJ7fK2zYs4JY6EE0PdfyazZP51imUnlFqUbIOyVQt9KqZwNnv+PPx3K+LFuFAl341sXTpPfoGcojO+/vDPvk4MW7WvG916utV4xjZ+/uQ8/1jLzl1jkdTxnEPima+lMBOdG65zVDf5PDfoTQyrM6kamCwzLS521Hn/r2W340mMb0TMURmufcWB/1bxVjrbpVDgac+WzY3TcEgnVj7T0Jc0ETfj9eyexrq4Nn3lgXVKrXCaTd7zMzqfiYgBNur9Pa8sM11FKRQD0AJiR5rGW29S6Ob8JYJnRTonId0WkVkRq29qM+6xptNQrO7uKpTxJvmWTEVzluayAGyesn7y+14U9cddPF+zFR/5jBd6obbJeOYfyfTztStfN/+q2Riw72IKnHRbGztbNr+0ertOZqddrm/BHbRZ0YpyY2Wc8kdpGL90M0MQPvdH2mnStdTGVXIXjZPsAlFKjWoZH1jd/Tqdd/Me1Vq6/uXs1rpq32nBSQrqWODd87+WdrkwsS/e+NHcPpU2lkjqrXt962Gcy4/501yA2Hy+OsWlenjjwJIANSqn3jO5USj2tlJqjlJozc+bMPO/a+PObVcktcF79QbLDzVIrv3hnv6P1jQKJfNTXfmHTSfzlrcuSxmsAwI3Pb8d/yfHVdibuWmI9Oy8hkejy9zbHiuWK0e/MoeZe3PzarqTs6kop/Hj+bmzK0wDmtDMKtc67Qs18jmlVN/7bk87GW6UGT1YVUoxafdMFBoluSasehEgsltSarpQaTjKccLx1pMsw3anHTpBmFFgOaAPlf/L6HsvHu+lk+0BWrcX6l5Iuma3T0/Xbu0YS3/6vl4xba//hgXX4xu+LY2yanSDtDIBLdX9foi0zXEdE/ACmAOhI89i02xSR/wdgJoCf2nkRlHt/SBmk+an71xVmR1zgZqvg0XPOZow+XqDi9E+sO45QNIbeoeQgbW1d26gZaF6QSVoJO92vCsA3n92G6prFGHCpmoF+26l+OH83Fu07ixPtA3hoRR3WH21DNKbwxz3N+LHBj6q+RJhbwmla0uq0sleLXCiLlon2gfhx3nXK2czF/pQWkpLhoMp4feMgzXz7ie7On7+1H196zLCdIL6NGDBBl/4hpkZXqUgN4szYuVZL7LPRdvJ9DI3G62UqfTDsfoNA4jtRDOWm7ARpOwDMEpHLRaQM8YkAC1PWWQjgBu32tQDWaGPKFgK4Tpv9eTmAWYiPMzPdpoh8B8DVAK5XKnW4OhVKLgbdF4pb4xRSW6XsMEqOGo4qwzEzbkqMVx7L3dZ2X9l7x+ItWF9/akvudkbj03WbPbqmHjc8NzJbzig4vnvpEdf3IWLQTBGJxnDvsiNosJliIROJ5LML0nRDO0kWrD8Hpb6mxHaMZmMCxoFquhb1xPba+oJph4gopVBe6ktaVpLmV9Vs0oldiXPXgyvMc8XZcbC5B9U1i7GzMbOqC4C7PQDp06G49zyp3i2CpOGWQZo2xuxmAMsBHAawQCl1UETuEJEva6s9C2CGiNQj3vpVoz32IIAFAA4hPrbsB0qpqNk2tW09BeACAFtEZI+I3ObSayUC4F7Auf+089JN+vOa/uTz2rbcJYYFRlqm3OzqBcx/FAvBzuSW3adG6lyapSZw8x1KtPAUcgBzODL6uY+19uO3645jT5q0O9lK5NH72Zv7TNdxEqQdOTsy9iv1O5wIhlO7GhNC0dE5z9J9XgYdJIBNnpWpcOm0qqT77aSq+eivV+Lf37Qe75nY5/k7sjtfJC5UVmQxLtBpNY500n097Hxz0q0TisTQ0R80bDUzGqvoNbbGpGkzLj+glPpzpdQ8bdltSqmF2u2AUurrSqkrlFJXKaVO6B47T3vcXyillqbbprbcry37K+3fHe69XLLSbvJhHiuqaxYn/VBnau2RVsepEpYdiHd7JayrG5nwkov6i8FIFLe8vS9piro+WMh2ej5g/qOYDyfbB/AjbXYfYO+Kc99DAAAgAElEQVSK+/lNDTnbH6PvTeL3O12W/HTszqqua+kzbY01mt3pNDGqHbGYws/e3DtcR9HOjFsns6P142Df3ZM84ibRemX2HrQa1sU0f66NNscLNvcE8N9/N9Ii+/1XdmFCeXL6GKtuwWUHWtA5EEJTp/UFj1sXmImW9d85mDASisTwuYfWY9E+bbKGwyDtqnmrcI9JS7FVYmErc+40H1f7gV8txcfuXGV4rqptyP63INe8PHGACuAP204l1VQbi775bPYJGm98YYfhmKJ0vv/KrpS/R1KC5KKhZen+Fvxhe1NSiRx9d+fzGxuyfo5Cpmb5+Zv7krorvHhtkWjhyXSAtd3umKsf2YC/vmu14X1Gszt//pazCS92LNp/FgtqT+OT960FgLTdnAlfecL+hAF99/BdS5J/7CdqgZHZ+MpygwoWGX92Ux6WWgw+tTqL1RCDe5ba7wJNXGRlm+E/k1aw/mAE9a39+PWieFoap5to7QviKZMxl+la+N06N76+Y/TncXcTgzQqMukKAFMyJ+d4q6tBs27Dc70BW/UmjSzXpq3rW8+SS6mkf7xSCm/tPJ229p/Ry6pv7U+qXrFoX3NGXcNWUn8keofCuOaRDa60EGbC6AiXGCQvddLFeOxc9tUHUltpd2XZknzgTA/O9QaSZqwCo4vXt7o8IeWmF83zqv3ZjAkAzH/QjRa7+f3VS030/d7R9K1y4iDaicXcyQmof079a1t+sAXv7D6d9rGJoRNuJvJO9+66NcHHKCjPdYoSNzBIoyR/2F7YXFNjldU53qw26l/ftRr/8MC6jJ5z6YF4kKZ/av1VfX8w/bibzcc78G9v7MW8JeYJXY1OfJ97aD3m6lpIbn5tN77xjHld2ASzWolmUqsB9AUjONLShw/fvsLkEflnNKvw2jxMWNDTJzrdVN+O/2aSaNWOrSc68KXHNuKv71qN2/90MOk+N8coOZUukz9g/P1z0pJmt/sTGOlKtMvJ2xaJKWxJKSOWCf0+6lsCv/fyTtu5EH/+lvlYQzc5TfJr5nieqie4jUEajZKu1AhlxurnwO2B5foWs5PtI4Nj9c9j9eOQSAS5s9G85ae52964PLOkknovbm5wFKilCwqiMYXnMhwvl+n4QKPWFi9kPK8qGxkjle14TH2LaGpXbKFitFhMpU0zAhgHZE6OTWrqmnRSW8ZSn0Vf4PuuJYctSy/pW7ZiSrnyPpcktaSNvt/os7w/5XfBbivUvcuODE8iyYQXhzHkU24K5FFR+9pv83ulPx5YzYKMxtSo4EB/ouweDGFqVZnt5/vVuweGb+tTCOjHkPtsnu1Ta0vqrTqcXdZ4vbuXHkFj5yDu+uqHbK1v1JWY8OzGE6PGLdl15a2GRU4s3fbuwVHLrFprqmsWp73/iMNi63/+iyW4dFol/s9nZhne76Rrzcg8XZLh1MBb/1Kdtopm4+pHNuBYa/pZesYtafafIxKLIRSJWbbYAbAMSL7xzDas+umnAChblR70LVvdg2Fb+2BFvwmjz6jRfunTx9jV1DmI364zHodmN/ga70EaW9KI8sBq/EbEMEgbuW1Uuy4ds5Qe+u5Oo+LhhbYiTfmXVL40u7+3Kf+twZsNuqHOn1SR1TadpsiIxhQaOgZNZ5Pmq0vSjXqOcx/faGs9qwANMK6Qkj5PWvLfkajCB361FP/2xl7LrLNmJaH0eoZCjtJ8JPzXxzemvTixTfc5SLwN+nOUUaF6u/SttUYFzpu7hxy1Yua6us1tugtaL2KQRpQHVi0YRids/anp1W2NuHNR5sW+E/RBkD5I6xwI4dP3r8Xm4+0YCEbwl7cuw3ObRroLb3w++xmxdjhp3UgXcCze7zz7+mOrjzkuT2SlssxnvVIO6AOFaEzh3mVH0D0YQveQ/eCprqUP1TWLM0rX4cbP6l4XJ5vEVDxdjD5li5GXtzbivz+1ZdRnK5E8N1GCzAmjT2k4qjIKmEORmO0W8HT0cV6ixb6xY6TbNZtUH/qg2Sie/Jt71uCRVfZT0mw9kXnCXTte2tLoev5INzFII/IAo4kD+u7O3793Es/YHGOVbibay1sbh2/rg7SDzT1o6Ih3TZxoG8BQOIrtJ0dOjmvr2vKSP8+o68XsBOpKi4LOgyuPOi5PZOWoC7Mzs7XmSCt+u+44bnv3IN7ZZT/IuPqRDQDiBezt0B8lr/3oKQX8etEhy5Qmt/7xALY3dI4KoIxaSe0yarGOxlTGLdludHf6DMaktfTo8ylmPutR33pmFogmJjV5hZcrsTBII8oDqxJSRqVnjLoKWnqsB+qny6Gkz5mlP4Em0gbsbeqG36Qf0WygsNkPslIqKbAzCvJSx+oZdev+6PU9qDGYSebB3tpRGnNUdmldnf28a4kWkubuoYxauPQtLHaZ/eaFIjFHsxPdujBwnBMt5bOVFNw53JRR115fIJxxkObGxUlJUndnfP9Kdd97q89tuhbJkI0grT6li/rf39ibdEGT74TqXpjgY4ZBGlEevLXTeTeJUZ2/v7t3jeXjygwSdyboT0b6c33iXNobiCSdrPXMxtosNxlH1tYXTCq9ZJTvTZ/Q18yf9jZjvkEiSjszRnOlzuGAfrf9y/M7bK+7Q8uq3tg5mNEgbKuZk0bMxhG9uq0R1//eOh1LgpOKBE6lG+s03cEkHStGAWIklll3p2uSJg7E/9cHjVZBbboWSX2QZvclNnYM4gevjiT7NktKnCterk3NII0oD3ocjAVK0KfOSLBzMkl3YtSffPXr6R/iN6kQbZZUcsBkAHQ4ppJO2Eb77nSA+d6mbvRpyWqtUhfk0tWPbCi6VDVVZb68VYgw+5gebDafKWzEKM9cJpy2lKTLzeV0W0af+9beYEEn7uhfg9utVvqhG04ScduZcJErO052YtG+Zrx3rA3zt+e2jrJTDNKI8mDVYevuqY6UbspcDJjVn46Tzs2634tSk5Y4sxmq9y0zTnURjSa3VRiVJzKaRdZjMpP1RFs/5j6xCR/SktW6MYMwGze/tst6JQ9p7BjMOEizU4g6tWvbqMvszZ3ps9mn+seHN+BPe+2VxkrHTu1UfZUMo89qgtMkrkZd+HcsOuTK2LJM/eKdkbJgbjci6QPrbzlI25HJbFe33PjCDtz82m5889ntqHnb/ZJp2WCQRuQRmYxfemB5naNZn2Y/0vquF7PZY6UmdaTMyv9EYrGkQNBugNAXNA7SUgva53pqvpWGHI03yyWnqVwSnAZXbv7w/2b1Mfc2prOgNvk16Wexpkto3OHw4sCobihQ2BQ4+q/i6a7Rn2P9/anlv6zYbf0s9Pe3WDBIIyoyv99wYrim4+Nr623P+gSST74NugHhdgqAr3aYuDYaS544kNpNZD7hwHh7+mSx33u5NqOxUpSZDod1Gt/e5SyoSyfTChB2rNIlntWnyXGz7qhZN17XYGYtwW73WNdZzEBOLSBvxe756PuvFFdLdKEwSCPyiAGLGaAJ85Ycxk8W7Mn6+fR1Wu1kPn9xS6PlOnqRWEp3Z0pQZlYo2mzMj35G2PKD7lU6IGuprU5WnjTIMm9Wn9ZKLsfRfeelkaLt+R7In02pJDclvm5mb/NLWxozypVnJV0lk0JffnlptieDNCKPcDKA9/BZ86tfr6T8ibekjfxt98fWKPUIFb9MC7tnkbLLkXz3Pnoll1y31n0b0rVY6vfs/uV1+PLjzpI872nqzmkLaK55ad8ZpBF5xHEHsxVTr/R+8OouVNcsdpQ/K1cSY20iMZUUmK2va7P1+P/6mL1yQFR4rX3WefsSnM7sTDjTPZTTVqdebbZwvjNiZJr2we2xXA9qkyr+96vudT9+5YlNeGFTg2vbyze2pBHRKIcy/BEDRsogveUgo7yZbLNvJ4K0aMrEgQ3HkoM0s2cJeegqltI7aJCEORde3easq92JxKzqbIvPO5VpIPC2C9/xfHhgRV2hdyFjXsqb5i/0DhBRnNMmdqPukqDNQb7pxgc5HSSe2JdEJnR/iSCEeBoD/VV/vhNUkruMSlzpj6+TnFhO5fI382BzD/ad7s77mLQ/7sks2HI60zYTOxu7rFeyUMzDFtiSRkSjOA3S7l0+Oj+Z3VaojcfaTe973SC7v5VtujqfIy1pyjPj4yh7//TwhlHL9Mf31W25SwKayzJBN7+2Gz+av8ewEHounevlRYuZQp83IvkaCGkDgzQij3DaxN5kUDInaFJfc9R6aa5yM0kNoK9NmgjSwilBWuqPYL7r85H77H5knebaGv08uf+s5KsaA3kfW9KIaBSnPxJGF3tbTtgrXp1ukHAmCU/1JzV9MNaZYS6ofMllF10xc3sMWG+WdVY31dsvyp4pO2loKPceWlGHj9+9uqD7kK7iRL4xSCPyCKfJWXN15W+Wvywdo31p7h7C4n3Zl/TJpcdylM2+2P3ynQOubq8YWqmOtVqXvqLce3RNfaF3gS1pRDSa07xJpqtneX7J5ARl1FV7i0UNPC+cBjmTNDt2u6yLIUgjSjjbYz+1TK4xSCPyiFqHM6qMxqQBwEfuWJHVfhxpSV8mxsjNr+02XH7exPLh2809AVTXLB4uZL3jpPsF5J1atO8sqmsWeyaxaLH57ss78bFfr7Qec8a3l2xwkncvl/KdMy8dBmlERcqq5p6ZPU3ul3gx86kPzBy1LDFubmO9+QzTfAt7aDZXoaw/2pZRsNoxEEKXxThGxmhkR6tHZrz+l+rphd6FYQzSiMaZrzzhrMSLXbGYQl8gjIHgSA42o9/8RM+Xl364GaMBNzy3Hc9vbsjosVbdmezuJDu8MvzAl+8aYWkwmS0RuWLeksN4duPJpGVPrB09CNjtsjZu2Hoy97MHi4FZF7oVq/Qx7E0mOw6e6Sn0LngOW9KIyBWpARoA7Dc46Q63pHnoh3vrcQZpQOYtXlGLmcnMiUd29AftVUwZTxikEVGBeOeH+3fMkQUg88DZqt4rYzSyY0Gt82onYx2DNCLKq4PN7NLwquNtmeUKi1oM6iuWouBUWEwuPRqDNCLKq5PtmY17otzbdzqzANpqvPfDq45mtF2i8Y5BGhHlVSAcH3fCLjDvyXRMmpcKUhONJQzSiCivEl0aDNK8JxyNDQfRTmRSSoy842iGORcp9xikEVFelfq8k4OIkoWjCme6hxw/roFd2EXtRIZjESn3GKQRUV45LSRP3mc1u5O8bSiD1lPKDyazJaK8q65ZXOhdIBPLDrQ4fszhs7052BPKl9OdzltPKT/YkkZERMPuX17n+DGvbTuVgz2hfCn1MxTwKh4ZIiIiIg9ikEZERDSO3bP0SKF3gUwwSCMiIiLyIAZpRERERB7EII2IiIjIgxikEREREXkQgzQiIiIiD2KQRkRERORBDNKIiIiIPIhBGhEREZEH2QrSROQaEakTkXoRqTG4v1xEXtfu3yYi1br7btGW14nI1VbbFJGbtWVKRM7L7uURERERFSfLIE1EfACeAPB5ALMBXC8is1NWuwlAl1LqCgAPA7hXe+xsANcB+CCAawA8KSI+i21uAvA5AI1ZvjYiIiKiomWnJe0qAPVKqRNKqRCA+QDmpqwzF8CL2u03AXxWRERbPl8pFVRKnQRQr23PdJtKqd1KqYYsXxcRERFRUbMTpF0MoEn392ltmeE6SqkIgB4AM9I81s42iYiIiMatop04ICLfFZFaEalta2sr9O4QERERucpOkHYGwKW6vy/RlhmuIyJ+AFMAdKR5rJ1tpqWUelopNUcpNWfmzJlOHkpERETkeXaCtB0AZonI5SJShvhEgIUp6ywEcIN2+1oAa5RSSlt+nTb783IAswBst7lNIiIionHLMkjTxpjdDGA5gMMAFiilDorIHSLyZW21ZwHMEJF6AD8FUKM99iCABQAOAVgG4AdKqajZNgFARH4oIqcRb13bJyLPuPdyiYiIiIqDxBu8itucOXNUbW1tzrZfXbM4Z9smIiIi72i454s5fw4R2amUmmO1XtFOHCAiIiIayxikEREREXkQgzQiIiIiD2KQRkRERORBDNKIiIiIPIhBGhEREZEHMUgjIiIi8iAGaUREREQexCCNiIiIyIMYpBERERF5EIM0IiIiIg9ikEZERETkQQzSiIiIiDyIQRoRERGRBzFIIyIiIvIgBmlEREREHsQgjYiIiMiDGKQREREReRCDNCIiIiIPYpBGRERE5EEM0oiIiIg8iEEaERERkQcxSCMiIiLyIAZpRERERB7EII2IiIjIgxikEREREXkQgzQiIiIiD2KQRkRERORBDNKIiIiIPIhBGhEREZEHMUgjIiIi8iAGaUREREQexCCNiIiIyIMYpBERERF5EIM0IiIiIg9ikEZERETkQQzSiIiIiDyIQRoRERGRBzFIIyIiIvIgBmlEREREHsQgjYiIiMiDGKQREREReRCDNCIiIiIPYpBGRERE5EEM0oiIiIg8iEEaERERkQcxSCMiIiLyIAZpRERERB7EII2IiIjIg2wFaSJyjYjUiUi9iNQY3F8uIq9r928TkWrdfbdoy+tE5GqrbYrI5do26rVtlmX3EomIiIiKj2WQJiI+AE8A+DyA2QCuF5HZKavdBKBLKXUFgIcB3Ks9djaA6wB8EMA1AJ4UEZ/FNu8F8LC2rS5t20RERETjip2WtKsA1CulTiilQgDmA5ibss5cAC9qt98E8FkREW35fKVUUCl1EkC9tj3DbWqP+Yy2DWjb/ErmL4+IiIioONkJ0i4G0KT7+7S2zHAdpVQEQA+AGWkea7Z8BoBubRtmzwUAEJHvikitiNS2tbXZeBlERERExcNf6B3IlFLqaQBPA8CcOXNULp/r+F1fwObj7fCJYOakcnQOhDAQiqBEBPWt/RgKRXHepHJMqypF12AYZ7qGMG1CGfY0deODF02Gv0QwpbIU53oDeN+USgyEIjje2o+LplbiwikV6BoIoaLUh6FwFFOrShGOKJzrDWDahDK09wehFBBTClecPxGBcBQTyv2IxhTa+0PwCdAbiKA/GN+fmdp+NHUO4YLJ5RgIRVHuL0HXQAjV501A12AIkahCIBJFVakPgUgMl06rQigaRTiqUFnqgwIQDEfhKxGc6RrC+6ZWonswhMoyH4ZCUUyfUIZpE8pwvLUfzd0BVJaV4ILJFejoD+GiqRUQEfQHIrjywkk4dLYXVWV+VJX5cLprEFVlfkys8CMYiSEYju8bRHDwTA8unV6FKZWlw6+x3F+Csz0BlIjgAxdMRGtfEF2DIcycWI7BUBR+n6DMVzK8v0PhKGZMKEf3UBgfungKBoIRXHH+RCw/2ILzJ1egqtSHSExhWlUpGjsHcby1H9MmlOH8SfHtTZ9Qhp6hMDoHQphU4UcspjCpohTdQ2GU+UswtbIUADB9Qhl6h8JQAALa+3S2J4DLplfhTNcQrrhgIkpEcKpzEJWlPkRjMUytKoNSCuX++Pswc1IFgpEogpEYJleUYnKFHxPK/WjqGkTXQAhXXT4Dg6EIOvrjx622oRMxBVwyrRLhaAyRmML5k8rR2hdEiQj6AmEoBVw4pQKhSAwAIAJEogoDoQhiSiEWA/oCYVw2owrlfh98JfHjVF5agr5ABH2BMKZUlmFKZSmCkSiUAtr6gqgs8+GiqZU43TWovd4S+EqAQDiGmRPLUVICtPQEMRCMYMbE+OMvnFKBs90BBCMxDIWjmFThh08EJSXAUCiGvkAYV5w/Ee39IRw624vzJ5UjEo3hshlVaOkJYmKFH2U+weSKUhxu6cPUylJMm1AKgSAUjSEaUxgMRVE9owrt/SEMBCM40z2Ey6ZXocxfgonlfvQFIvCVAH2BCKZUliISU4jEFKZWlqKupQ/nTYoPdy0RwfvPm4j9Z3rw4Uum4HhbP5QC+oMRTKsqQ0wpDIYi6BwIY0K5DxdMroBSwMxJ5QiEo+gLRDCtqhThqEJvIIwTbf14/8yJuOL8iWjqHERJiaCzP4QyfwkmlPsQjR8e9A6FMbHCj66BEM6bWI6LplaiNxBGqU9wvG0A4WgMl02vwpGzfbh0eiW6BsO4cHIFIPHjMrHcj+7BMPwlggnlfvQFwigvLUEoEoOIYFK5HxdMqcDhs72YXlWGmALO9QZQVebDjInlKBGgpEQQDMdw4ZQKtPcFMbWqFH5fCVp6Aogphfb+ICZXlKK1L4A/mzEBSgGRWAwCgYLCeRPLMaHMj+aeISgF+Eok/rkOxxCJxdDaG8TkylLMOn8imnsCAIBSn6C9P4SPXDIFvhJBR38IvhLBUDiKyjIfAqEoBkNRzLpgIroGw+geDKF6xgRElULXQAglIqgq86GlN4DBUPz7d97EMvhLStAfjKC9P4hLplUOfwcvP28CAuEYBoIRXDq9Cn2BMMJRhRIBWnoDuGhKJYKR+HNOm1CG6VVlqGvpw/QJZYgqhUkVfpzrjZ+HJpb74feVoL61H+dNLEOJCPqDEbxvSgUmVfjR0hOE3ydQSuFcbxB/denU4f2OxBS6B0O44vyJ6B4MY9qEsuHjGAhH0dYXREWpD6W+Ekys8KPUJ+gdin8vS0Tg9wmCkRhmTChDVZkfB8704K8um4pAOP5drSrz4WxPAIFwFFVlfvQGwrh4aiWA+HGfVlWGrsEQPnjRFAyGIjjdNYRwNIY/mxH/XSjzx88DVaU+TKzw41hrPz508RR0DYRQ6itBW38A/pISVJb6MLmyFNGYwkAwgqFwFNGYQjSmUF5agp6hMN43pQJ9gQjKfCVo7QvigskVaO8PYlJF/LVWlPowY0I5wtEYJpT70dYXRJm/BNGYAqBw5YWTsbupCwAwY0I5egNhhKPxc2XPUBilvhKU+gQ9Q2H0B6OYUlmKaVWlKPOX4FTnIMp8JZg5qRxDoSja+oOoKou/n92DYVw4pQJKKUyuiP8OXDi5ApVl8ff9XG8A/+miKbkMJxwTpdLHNyLyCQC3K6Wu1v6+BQCUUnfr1lmurbNFRPwAWgDMBFCjXzexnvawUdsEcA+ANgAXKqUiqc9tZs6cOaq2ttb2iyYiIiIqFBHZqZSaY7Wene7OHQBmabMuyxCfCLAwZZ2FAG7Qbl8LYI2KR38LAVynzf68HMAsANvNtqk9Zq22DWjbfNfGPhIRERGNKZbdnVqL1s0AlgPwAXhOKXVQRO4AUKuUWgjgWQAvi0g9gE7Egy5o6y0AcAhABMAPlFJRADDapvaUPwcwX0TuBLBb2zYRERHRuGLZ3VkM2N1JRERExcLN7k4iIiIiyjMGaUREREQexCCNiIiIyIMYpBERERF5EIM0IiIiIg9ikEZERETkQQzSiIiIiDxoTORJE5E2AI05fIrzALTncPuUHR4fb+Px8T4eI2/j8fG2TI7PnymlZlqtNCaCtFwTkVo7SeeoMHh8vI3Hx/t4jLyNx8fbcnl82N1JRERE5EEM0oiIiIg8iEGaPU8XegcoLR4fb+Px8T4eI2/j8fG2nB0fjkkjIiIi8iC2pBERERF5EIM0IiIiIg9ikGZBRK4RkToRqReRmkLvz1gmIs+JSKuIHNAtmy4iK0XkmPb/NG25iMij2nHZJyIf1T3mBm39YyJyg275x0Rkv/aYR0VE8vsKi5eIXCoia0XkkIgcFJEfact5fDxCRCpEZLuI7NWO0X9oyy8XkW3a+/q6iJRpy8u1v+u1+6t127pFW14nIlfrlvN8mAUR8YnIbhFZpP3NY+MhItKgnYP2iEittqyw5zilFP+Z/APgA3AcwPsBlAHYC2B2ofdrrP4D8PcAPgrggG7ZfQBqtNs1AO7Vbn8BwFIAAuDjALZpy6cDOKH9P027PU27b7u2rmiP/XyhX3Ox/APwPgAf1W5PAnAUwGweH+/80963idrtUgDbtPdzAYDrtOVPAfhX7fb/BvCUdvs6AK9rt2dr57pyAJdr50Afz4euHKOfAngNwCLtbx4bD/0D0ADgvJRlBT3HsSUtvasA1CulTiilQgDmA5hb4H0as5RSGwB0piyeC+BF7faLAL6iW/6SitsKYKqIvA/A1QBWKqU6lVJdAFYCuEa7b7JSaquKf1te0m2LLCilziqldmm3+wAcBnAxeHw8Q3uv+7U/S7V/CsBnALypLU89Rolj9yaAz2pX9nMBzFdKBZVSJwHUI34u5PkwCyJyCYAvAnhG+1vAY1MMCnqOY5CW3sUAmnR/n9aWUf5coJQ6q91uAXCBdtvs2KRbftpgOTmkdb38Z8Rbanh8PETrTtsDoBXxH4fjALqVUhFtFf37OnwstPt7AMyA82NH9jwC4GcAYtrfM8Bj4zUKwAoR2Ski39WWFfQc53f6CogKRSmlRIQ5YwpIRCYCeAvAj5VSvfohFTw+haeUigL4KxGZCuAdAFcWeJcIgIh8CUCrUmqniHy60PtDpv5OKXVGRM4HsFJEjujvLMQ5ji1p6Z0BcKnu70u0ZZQ/57RmYmj/t2rLzY5NuuWXGCwnm0SkFPEA7VWl1NvaYh4fD1JKdQNYC+ATiHfDJC7I9e/r8LHQ7p8CoAPOjx1Z+1sAXxaRBsS7Ij8D4DfgsfEUpdQZ7f9WxC9yrkKBz3EM0tLbAWCWNgOnDPEBnAsLvE/jzUIAidkxNwB4V7f8W9oMm48D6NGapJcD+CcRmabNwvknAMu1+3pF5OPa2I5v6bZFFrT37FkAh5VSD+nu4vHxCBGZqbWgQUQqAfwj4mMH1wK4Vlst9Rgljt21ANZoY2UWArhOm2F4OYBZiA945vkwQ0qpW5RSlyilqhF/39Yopf4HeGw8Q0QmiMikxG3Ez00HUOhzXL5nTxTbP8RncBxFfGzHLwu9P2P5H4A/ADgLIIx4f/1NiI/DWA3gGIBVAKZr6wqAJ7Tjsh/AHN12vo34gNp6ADfqls/RvnTHATwOreIG/9k6Nn+H+HiNfQD2aP++wOPjnX8APgxgt3aMDgC4TVv+fsR/yOsBvAGgXFteof1dr93/ft22fqkdhzroZqDxfOjKcfo0RmZ38th45J92LMQUK0gAAABOSURBVPZq/w4m3sNCn+NYFoqIiIjIg9jdSURERORBDNKIiIiIPIhBGhEREZEHMUgjIiIi8iAGaUREREQexCCNiIiIyIMYpBERERF50P8HKklAU5kNZAsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mlfinlab.features.microstructural import corwin_shultz_spread, becker_parkinson_volatility\n",
    "spread, start_ind = corwin_shultz_spread(bars.high, bars.low, 100)\n",
    "vol = becker_parkinson_volatility(bars.high, bars.low, 100)\n",
    "\n",
    "plt.figure(figsize=(10, 5))\n",
    "spread.plot()\n",
    "plt.figure(figsize=(10, 5))\n",
    "vol.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Second generation: strategic trade models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Kyle's Lambda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data in batches:\n",
      "Batch number: 0\n",
      "Returning bars \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1bcc0d30>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mlfinlab.data_structures import BarFeature\n",
    "from mlfinlab.features.microstructural import kyles_lambda, dollar_volume\n",
    "\n",
    "kyles_lambda_feature = BarFeature(name='kyles_lambda', function= lambda df: kyles_lambda(df['price'], df['volume']))\n",
    "bars = get_dollar_bars('./maks_tick_data.csv', threshold=70000000, batch_size=1000000,\n",
    "                       additional_features=[kyles_lambda_feature])\n",
    "\n",
    "plt.figure(figsize=(10, 5))\n",
    "bars['kyles_lambda'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Amihud's Lambda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data in batches:\n",
      "Batch number: 0\n",
      "Returning bars \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "6.600161489263962e-10"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mlfinlab.features.microstructural import dollar_volume, amihuds_lambda\n",
    "dollar_volume_feature = BarFeature(name='dollar_volume', function= lambda df: dollar_volume(df['price'], df['volume']))\n",
    "bars = get_dollar_bars('./maks_tick_data.csv', threshold=70000000, batch_size=1000000,\n",
    "                       additional_features=[dollar_volume_feature])\n",
    "lambda_ = amihuds_lambda(bars['close'], bars['dollar_volume'])\n",
    "lambda_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hasbrouck's Lambda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data in batches:\n",
      "Batch number: 0\n",
      "Returning bars \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.4467778933355137e-08"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mlfinlab.features.microstructural import dollar_volume, hasbroucks_lambda, hasbroucks_flow\n",
    "\n",
    "def get_hasbroucks_flow(df):\n",
    "    tick_signs = tick_rule(df['price'])\n",
    "    return hasbroucks_flow(df['price'], df['volume'], tick_signs)\n",
    "\n",
    "hasbroucks_flow_feature = BarFeature(name='hasbroucks_flow', function=get_hasbroucks_flow)\n",
    "bars = get_dollar_bars('./maks_tick_data.csv', threshold=70000000, batch_size=1000000,\n",
    "                       additional_features=[hasbroucks_flow_feature])\n",
    "\n",
    "lambda_ = hasbroucks_lambda(bars['close'], bars['hasbroucks_flow'])\n",
    "lambda_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Third generation: sequential trade models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Volume-Synchronized Probability of Informed Trading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data in batches:\n",
      "Batch number: 0\n",
      "Returning bars \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1a756048>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mlfinlab.features.microstructural import vpin\n",
    "from mlfinlab.data_structures import get_volume_bars\n",
    "\n",
    "def buy_volume(df):\n",
    "    tick_signs = tick_rule(df['price'])\n",
    "    return (df['volume'] * (tick_signs > 0)).sum()\n",
    "\n",
    "def sell_volume(df):\n",
    "    tick_signs = tick_rule(df['price'])\n",
    "    return (df['volume'] * (tick_signs < 0)).sum()\n",
    "    \n",
    "buy_volume_feature = BarFeature(name='buy_volume', function=buy_volume)\n",
    "sell_volume_feature = BarFeature(name='sell_volume', function=sell_volume)\n",
    "\n",
    "bars = get_volume_bars('./maks_tick_data.csv', additional_features=[buy_volume_feature, sell_volume_feature])\n",
    "volume = 28224\n",
    "vpin_series = vpin(bars['buy_volume'], bars['sell_volume'], volume, 5)\n",
    "plt.figure(figsize=(10, 5))\n",
    "vpin_series.plot()\n",
    "plt.figure(figsize=(10, 5))\n",
    "bars['close'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Additional Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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